On successful completion of the course, the student should:
- know the main classes of distributed computing approaches, with in-depth knowledge in selected techniques from each class
- have knowledge of cloud computing, benefits, challenges, deployment and communication
- have acquired competence in big data analysis, decomposition, computing and multilevel search
- be able to cast traditional problems in a distributed computing perspective
- be able to analyze, implement and evaluate distributed computing solutions
- have obtained skills in applying distributed computing in new domains
- understand how big data infrastructures rely on distributed computing principles
- have acquired competence in extracting and presenting knowledge from the distributed computing research literature
The course covers the following distributed computing topics:
Design goals: transparency, openness, scalability.
Communication: remote procedure call, remote object invocation, message-oriented communication.
Processes: threads, clients, servers, code migration, software agents.
Naming: naming objects, locating Mobile Objects, Synchronization.
Consistency & replication. Fault tolerance. Security. Component Architectures. Distributed object-based systems. Distributed coordination based systems.
Big data: Data partitioning, Multilevel Techniques.
1 semester
7.5
Spring
Grimstad
Faculty of Engineering and Science